[jira] [Created] (SPARK-29372) Codegen grows beyond 64 KB for more columns in case of SupportsScanColumnarBatch

["Shubham Chaurasia (Jira)" <ji...@apache.org>]

Shubham Chaurasia created SPARK-29372:
-----------------------------------------

             Summary: Codegen grows beyond 64 KB for more columns in case of SupportsScanColumnarBatch
                 Key: SPARK-29372
                 URL: https://issues.apache.org/jira/browse/SPARK-29372
             Project: Spark
          Issue Type: Bug
          Components: Spark Core, SQL
    Affects Versions: 2.3.2
            Reporter: Shubham Chaurasia


In case of vectorized DSv2 readers i.e. if it implements {{SupportsScanColumnarBatch}} and number of columns is around(or greater than) 1000 then it throws

{code:java}
Caused by: org.codehaus.janino.InternalCompilerException: Code of method "processNext()V" of class "org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage0" grows beyond 64 KB
	at org.codehaus.janino.CodeContext.makeSpace(CodeContext.java:990)
	at org.codehaus.janino.CodeContext.write(CodeContext.java:899)
	at org.codehaus.janino.CodeContext.writeBranch(CodeContext.java:1016)
	at org.codehaus.janino.UnitCompiler.writeBranch(UnitCompiler.java:11911)
	at org.codehaus.janino.UnitCompiler.compileBoolean2(UnitCompiler.java:3675)
	at org.codehaus.janino.UnitCompiler.access$5500(UnitCompiler.java:212)
{code}

I can see from logs that it tries to disable Whole-stage codegen but it failing even after that on each retry.
{code}
19/10/07 20:49:35 WARN WholeStageCodegenExec: Whole-stage codegen disabled for plan (id=0):
 *(0) DataSourceV2Scan [column_0#3558, column_1#3559, column_2#3560, column_3#3561, column_4#3562, column_5#3563, column_6#3564, column_7#3565, column_8#3566, column_9#3567, column_10#3568, column_11#3569, column_12#3570, column_13#3571, column_14#3572, column_15#3573, column_16#3574, column_17#3575, column_18#3576, column_19#3577, column_20#3578, column_21#3579, column_22#3580, column_23#3581, ... 976 more fields], com.shubham.reader.MyDataSourceReader@5c7673b8
{code}

Repro code for a simple reader can be: 

{code:java}
public class MyDataSourceReader implements DataSourceReader, SupportsScanColumnarBatch {

  private StructType schema;

  private int numCols = 10;
  private int numRows = 10;
  private int numReaders = 1;

  public MyDataSourceReader(Map<String, String> options) {
    initOptions(options);
    System.out.println("MyDataSourceReader.MyDataSourceReader: Instantiated...." + this);
  }

  private void initOptions(Map<String, String> options) {
    String numColumns = options.get("num_columns");
    if (numColumns != null) {
      numCols = Integer.parseInt(numColumns);
    }

    String numRowsOption = options.get("num_rows_per_reader");
    if (numRowsOption != null) {
      numRows = Integer.parseInt(numRowsOption);
    }

    String readersOption = options.get("num_readers");
    if (readersOption != null) {
      numReaders = Integer.parseInt(readersOption);
    }
  }

  @Override public StructType readSchema() {
    final String colPrefix = "column_";
    StructField[] fields = new StructField[numCols];
    for (int i = 0; i < numCols; i++) {
      fields[i] = new StructField(colPrefix + i, DataTypes.IntegerType, true, Metadata.empty());
    }

    schema = new StructType(fields);
    return schema;
  }

  @Override public List<DataReaderFactory<ColumnarBatch>> createBatchDataReaderFactories() {
    System.out.println("MyDataSourceReader.createDataReaderFactories: " + numReaders);
    return new ArrayList<>();
  }
}
{code}

If I pass {{num_columns}} 1000 or greater, the issue appears.
{code:java}
spark.read.format("com.shubham.MyDataSource").option("num_columns", "1000").option("num_rows_per_reader", 2).option("num_readers", 1).load.show
{code}

Any fixes/workarounds for this? 

SPARK-16845 and SPARK-17092 are resolved but looks like they don't deal with the vectorized part.



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